In all the methods, we first hold out 20 base classes for validation and
hyperparameter tuning and then re-train on all the base classes with the best
found parameters.
For evaluation, we compute the correct localization (CorLoc)
rate [1]} and mean Average Precision (mAP) with IoU
overlap threshold of \(0.5\)  on the query image.
